Episode Details

This is exactly the right place to probe. Gromov-Wasserstein is genuinely dimension free. Partial and semi-relaxed are precisely the mechanisms for the abstention/coverage problem we have. Want me to make a new branch and run run_entropic_gwot and invoke semi-relaxed GWOT between your models’ RDMs?

Wtf does that even mean? Eh, could be interesting to see the result. Enter

A peculiar side effect of model intelligence in discovery-based research is that it's possible to run every statistical/quantitative analysis under the sun, burn millions of tokens and gain little intuition on how to make headway into your problem.[1]

Pre-AI, the effort associated with constructing a pipeline to run any meaningful quantitative analysis incurred a real cost. Indeed, it forced one to consider whether the analysis made any sense at all. People who had the necessary skills to execute were often thoughtful about their analysis by necessity. You couldn’t just apply Mendelian Randomisation if you didn't know of its existence; there was effort required to both articulate your question to search for the right tools and de-risk by considering whether a tool fit your question.[2] This forced one to earn some intuition for how it worked and what to expect. The pain [...]

The original text contained 6 footnotes which were omitted from this narration.

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First published:
May 31st, 2026

Source:
https://www.lesswrong.com/posts/L8YFcCw5ex3qjLyoJ/outrunning-your-headlights

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Narrated by TYPE III AUDIO.